• DocumentCode
    1799015
  • Title

    Video transcoding time prediction for proactive load balancing

  • Author

    Deneke, T. ; Haile, Habtegebreil ; Lafond, S. ; Lilius, Johan

  • Author_Institution
    Abo Akad. Univ., Abo, Finland
  • fYear
    2014
  • fDate
    14-18 July 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we present a method for predicting the transcoding time of videos given an input video stream and its transcoding parameters. Video transcoding time is treated as a random variable and is statistically predicted from past observations. Our proposed method predicts the transcoding time as a function of several parameters of the input and output video streams, and does not require any detailed information about the codec used. We show the effectiveness of our method via comparing the resulting predictions with the actual transcoding times on unseen video streams. Simulation results show that our prediction method enables a significantly better load balancing of transcoding jobs than classical load balancing methods.
  • Keywords
    prediction theory; resource allocation; transcoding; video coding; video streaming; input video stream; proactive load balancing; video transcoding time prediction; Bit rate; Codecs; Load management; Load modeling; Predictive models; Transcoding; YouTube; Load Balancing; Machine Learning; Prediction; Transcoding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo (ICME), 2014 IEEE International Conference on
  • Conference_Location
    Chengdu
  • Type

    conf

  • DOI
    10.1109/ICME.2014.6890256
  • Filename
    6890256